NEMS is the Neural Encoding Model System. It is helpful for fitting a mathematical model to time series data, plotting the model predictions, and comparing the predictive accuracy of multiple models. We use it to study computational models of how auditory stimuli are neurally encoded in mammalian brains, but it will probably work with your timeseries data as well.
git clone https://github.com/lbhb/nems
# Please make sure that the nems repo is in your path. This works for linux:
echo "export PYTHONPATH=\"\$PYTHONPATH:`pwd`/nems\"" >> ~/.bashrc
source ~/.bashrc
We have a good tutorial/template at scripts/demo_script.py. We recommend beginners make a copy of it and edit it as needed. You may run it with:
# Run the demo script
python3 scripts/demo_script.py
- Quick Start
- Organizing your Data
- Organizing your Models
- Fitting your Models
- Detailed Guides
- Architectural Diagram
- Creating your own modules
- Comparing your models with others
- Sharing modules, models, and data with others
- Contributing to NEMS
